The need for large and fast data stores in cloud computing has increased with widespread adoption of big data applications. These data stores need to be able to scale up to support hundreds of thousands of concurrent client operations per second, while still maintaining the data reliably. However, each of the big data applications in the cloud operates according to a different paradigm. For example, the Hadoop® paradigm is different from the SQL® paradigm, which is different from the Kafka™ paradigm. This has required that cloud computing providers dedicate different clusters to these different paradigms, resulting in inefficient use of the clusters and difficulty in managing a large variety of clusters.